Abstract: In order to estimate production of apple orchard quickly and accurately，a new method of apple trees production estimate was proposed，based on machine learning and the Hough transform，with visible light and thermal infrared image data obtained from one side of apple trees.The registration of visible light and thermal infrared temperature images which was obtained synchronously from thermal imaging camera，was achieved by affine transformation model，taking mature apple trees as research object.The classification and calculation of posterior probability were completed with support vector machine，using temperature information and RGB color band as four classification feature，which obviously improved effect of apple detection identification.After edge detection，Hough transform was adopted to accomplish identification marks and counting of apple images.The apple trees production was estimated through linear regression model with cross validation.In the case of apple color differences made by non-uniform illumination conditions，experimental results showed the new method of apple trees production estimate were effective with accurate rate higher than 80%，compared with measurement data from manual record，providing effective technical support for scientific management of orchard.